Agent Skills

apiclaw-skills

ZooData Skills - AI Agent skills for e-commerce data intelligence across Amazon, TikTok & beyond, plus open-web extraction

README.md

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ZooData Skills

The data infrastructure built for agents.
Currently powering Amazon commerce with 200M+ products, 1B+ reviews, and real-time signals.

Tests License API Discord Stars

Website • Get API Key • Discord • Quick Start • API Reference


What is ZooData?

ZooData is the data infrastructure built for agents. Not a scraping API. Not a human dashboard. A purpose-built data layer that gives your AI agents direct access to Amazon commerce signals — 200M+ indexed products, 2+ years of history, and 1B+ reviews pre-processed into structured insights. Clean JSON, real-time, agent-ready.

https://github.com/user-attachments/assets/305a161b-7a53-49b8-afdc-4469a4fbf361

Skills Overview

This repo contains 10 agent skills organized in two tiers:

🏗️ Foundation — data access and full-spectrum analysis:

Skill What It Does Input Output Key Advantage
📦 zoodata/ Direct access to 25 Amazon commerce and keyword-intelligence endpoints Keyword, category, ASIN, or brand Raw API data with field mapping and quirk documentation Complete API reference — every other skill builds on this
🎯 amazon-analysis/ 13 built-in selection modes + market research, competitor analysis, ASIN evaluation, pricing, category research Keyword/category/ASIN + intent Analysis findings, top products, ASIN deep dives, confidence-tagged insights Composite commands (report, opportunity) run multi-endpoint pipelines in one shot
🔎 amazon-keyword-traffic-analysis/ Keyword value and product traffic-health workflows built on 11 keyword intelligence endpoints Seed keyword, target keyword, ASIN, or ASIN + keyword Expansion tiers, keyword-value analysis, product traffic structure, trends, and health diagnosis Dedicated flows for keyword expansion, keyword analysis, and product traffic analysis
📊 amazon-market-analysis/ Discover market and product candidates, evaluate entry conditions, and track category changes Market question, category, or product opportunity brief Observed shortlist, conditional entry assessment, or bounded trend analysis One connected story with separate evidence and seller-decision boundaries

⚡ Specialized — purpose-built for specific workflows:

Skill What It Does Input Output Key Advantage
⚔️ amazon-competitor-intelligence-monitor/ Deep competitor intelligence — Full Scan or Quick Check with tiered alerts Keyword or ASIN(s), optionally your ASIN + competitor ASINs Competitor matrix, brand ranking, price map, 30-day trends, scores (1-100), tiered alerts Dual-mode (Full ~28-35 credits, Quick ~5-10) with three-tier alert system
📡 amazon-daily-market-radar/ Automated daily monitoring — price changes, new competitors, BSR movements, review spikes Your ASINs (1-10) + keyword RED/YELLOW/GREEN alerts, KPI dashboard, competitor movement, action items Set-and-forget with signal validation (7+ day trends vs single-day spikes)
✅ amazon-listing-audit-pro/ 8-dimension listing health check with optimization recommendations Your ASIN + keyword Score (X/100, A-F), 8-dimension scorecard, keyword gaps, priority fix list Actionable rewrites using high-frequency review language; bulk audit support
💰 amazon-pricing-command-center/ Data-driven pricing signals — auto-detects leaf category, analyzes pricing landscape One or more ASINs RAISE/HOLD/LOWER signal, price band heatmap, competitor price map, BuyBox analysis ASIN-only input (no keyword needed), Sales/Competition Ratio
💬 amazon-review-intelligence-extractor/ Deep consumer insights from 1B+ pre-analyzed reviews across 11 dimensions Single ASIN, multiple ASINs, or category keyword Pain points, buying factors, user profiles, usage patterns, differentiation roadmap 1B+ pre-analyzed reviews (95% token savings), 11 dimensions
🌐 web-extract/ Structured data extraction from public web pages and search results URL, search query, or site Structured JSON or page content Handles rendered pages and bounded site crawls

amazon-market-analysis is the unified market skill. The former amazon-market-entry-analyzer, amazon-market-trend-scanner, and amazon-opportunity-discoverer directories are retained as retired source only; their entrypoints are named RETIRED.md, so skill installers and publishers do not discover them.

Quick Start

1. Install the Skills

npx skills add SerendipityOneInc/ZooData-Skills

You'll be prompted to select which skills to install:

🏗️ Foundation:

  • ZooData — 25 Amazon Commerce and Keyword Intelligence Endpoints
  • Amazon Analysis — Full-Spectrum Research & Seller Intelligence
  • Amazon Keyword Intelligence — Expansion, Reverse ASIN & Monitoring
  • Amazon Market Analysis — Discovery, Entry & Change

⚡ Specialized:

  • Amazon Competitor Intelligence Monitor — Dual-mode competitive intelligence with tiered alerts
  • Amazon Daily Market Radar — Automated Monitoring & Alerts
  • Amazon Listing Audit Pro — 8-Dimension Health Check
  • Amazon Pricing Command Center — RAISE/HOLD/LOWER Signals
  • Amazon Review Intelligence Extractor — Consumer Insights from 1B+ Reviews
  • Web Extract — Structured public web data extraction

Or clone manually:

git clone https://github.com/SerendipityOneInc/ZooData-Skills.git

2. Set Your API Key

export ZOODATA_API_KEY='hms_live_xxx'   # Get yours free at zoodata.ai/en/api-keys

🎁 Free tier: 1,000 credits on signup. 1 credit = 1 API call. No credit card required.

3. Try It

Ask your AI agent:

"Analyze the competitive landscape for wireless earbuds under $50 on Amazon US"

Or use the CLI directly:

python amazon-analysis/scripts/zoodata.py products --keyword "wireless earbuds" --mode fast-movers

API Endpoints

Base URL: https://api.zoodata.ai/openapi/v2 Auth: Authorization: Bearer $ZOODATA_API_KEY Method: All endpoints use POST with JSON body

Endpoint Description Example Use Case
🔍 products/search Product search with 20+ filters (13 preset modes via the CLI) "Find running shoes under $80 with 4+ stars"
📊 markets/search Category discovery and exact snapshot — size, concentration, selected Top 100 pricing "How competitive is the yoga mat market?"
🧩 markets/structure-profile Brand, price and other Top 100 distributions "Which price bands account for sales?"
📅 markets/history Available month-end category-market trends "How has this category changed by month?"
🏷️ products/competitors Competitor discovery by keyword, brand, or ASIN "Who are the top sellers in this niche?"
⚡ realtime/product Real-time product details — reviews, features, variants "Get current details for ASIN B0D5CRV4KL"
💬 reviews/analysis AI-powered review insights — sentiment, pain points "What do customers love/hate about this product?"
📁 categories Amazon category tree navigation "Show subcategories under Electronics"
📈 products/price-band-overview Price band summary with best opportunity band "What's the best price range for yoga mats?"
📊 products/price-band-detail Full 5-band price distribution analysis "Show detailed price band breakdown for wireless earbuds"
🏢 products/brand-overview Top-brand concentration metrics (CR10) "How concentrated is the brand landscape?"
🏷️ products/brand-detail Per-brand breakdown with top products "Which brands dominate this category?"
📅 products/history Historical daily snapshots for ASINs "Show price and BSR history for this ASIN"

13 Product Search Modes

The skill CLI (zoodata.py --mode) provides 13 preset modes for different research strategies. Modes are expanded into concrete filter fields (monthlySalesMin, salesGrowthRateMin, …) on the client side — mode is not an API parameter, and sending it to /openapi/v2/products/search returns 422:

Mode Strategy Target
fast-movers High sales velocity Quick revenue
emerging Rising trends, low saturation Early movers
long-tail Niche keywords, steady demand Sustainable income
underserved High demand, few sellers Market gaps
new-release Recently launched products Trending items
fbm-friendly Suitable for merchant fulfillment Low-investment start
low-price Budget-friendly products Volume strategy
single-variant Simple listings, no variants Easy management
high-demand-low-barrier High sales, low review barrier Scalable entry
broad-catalog Wide product range analysis Category overview
selective-catalog Curated high-quality picks Premium selection
speculative High-risk, high-reward opportunities Aggressive strategy
top-bsr Best Seller Rank leaders Market leaders

Project Structure

├── zoodata/                              # Data layer skill (lightweight)
│   ├── SKILL.md                            # 25 Amazon and keyword endpoints, quick start
│   └── references/
│       └── openapi-reference.md            # API field reference
│
├── amazon-analysis/                      # Deep analysis skill
│   ├── SKILL.md                            # Intent routing, workflows, evaluation criteria
│   ├── references/
│   │   ├── reference.md                    # Full API reference
│   │   ├── execution-guide.md              # Step-by-step execution playbook
│   │   ├── scenarios-composite.md          # Comprehensive recommendations
│   │   ├── scenarios-eval.md               # Product evaluation, risk, reviews
│   │   ├── scenarios-pricing.md            # Pricing strategy
│   │   ├── scenarios-ops.md                # Market monitoring, alerts
│   │   ├── scenarios-expand.md             # Expansion, trends
│   │   └── scenarios-listing.md            # Listing writing, optimization
│   └── scripts/
│       └── zoodata.py                      # CLI — 8 subcommands, 13 preset modes
│
├── amazon-keyword-traffic-analysis/      # Keyword intelligence & traffic analysis
│   ├── SKILL.md
│   ├── README.md
│   └── references/
│       ├── reference.md                    # Keyword endpoint reference
│       ├── execution-guide.md              # Execution and monitoring rules
│       ├── scenarios-expand.md             # Keyword expansion
│       ├── scenarios-keyword-analysis.md   # Keyword value and trend analysis
│       └── scenarios-product-traffic-analysis.md # Product traffic health analysis
│
├── amazon-competitor-intelligence-monitor/  # Competitor intelligence & monitoring
│   ├── SKILL.md
│   ├── references/
│   │   └── reference.md
│   └── scripts/
│       └── zoodata.py
│
├── amazon-daily-market-radar/            # Daily market pulse & anomaly detection
│   ├── SKILL.md
│   ├── references/
│   │   └── reference.md
│   └── scripts/
│       └── zoodata.py
│
├── amazon-listing-audit-pro/             # Listing quality audit & optimization
│   ├── SKILL.md
│   ├── references/
│   │   └── reference.md
│   └── scripts/
│       └── zoodata.py
│
├── amazon-market-analysis/               # Market discovery, entry assessment & change
│   ├── SKILL.md
│   ├── references/
│   │   └── reference.md
│   └── scripts/
│       └── zoodata.py
│
├── amazon-pricing-command-center/        # Pricing strategy & competitive signals
│   ├── SKILL.md
│   ├── references/
│   │   └── reference.md
│   └── scripts/
│       └── zoodata.py
│
├── amazon-review-intelligence-extractor/    # Review intelligence & insight extraction
│   ├── SKILL.md
│   ├── references/
│   │   └── reference.md
│   └── scripts/
│       └── zoodata.py
│
├── web-extract/                          # Structured public web extraction
│   ├── SKILL.md
│   └── scripts/
│       └── webtools.py
│
├── scoring-methodology.md                # Unified quality scoring framework
├── CHANGELOG.md
└── README.md

Requirements

  • Python 3.8+ (stdlib only, zero pip dependencies)
  • ZooData API Key (get one free)

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Community

  • 💬 Discord — Chat, get help, share what you're building
  • 🐛 Issues — Bug reports and feature requests
  • 📖 API Docs — Full API documentation

License

MIT © SerendipityOne Inc.

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